A Framework to Quantify the Uncertainty Contribution of GCMs Over Multiple Sources in Hydrological Impacts of Climate Change

Wang, Huimin; Chen, Jie; Xu, Chong‐Yu; Zhang, Jianke; Chen, Hua

doi:10.1029/2020ef001602

Cited by 90 publications

(48 citation statements)

References 58 publications

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“…In addition, the average SDE and SDW obtained by NBM, AOM, and UFBM for each EF pattern are more similar than those obtained by FBCM, FAVM and YCRM. Many studies have investigated these uncertainties on watershed hydrology [18,35,36]. Zhang et al [37] investigated the overall uncertainty and the relative contribution of each uncertainty component for hydrological simulations over 408 watersheds in China by using 3 emission scenarios, 21 GCMs, 8 downscaling methods, 4 hydrological models, and 2 sets of optimized hydrological model parameters.…”

Section: Discussionmentioning

confidence: 99%

Assessing the Uncertainty of Hydropower-Environmental Conflict-Resolution Management under Climate Change

Hui

2021

Water

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To balance the water demands of different departments and produce a win–win result for reservoir operation, a series of conflict-resolution methods have been developed to define the socio-optimal operation strategy for specific conflict problems. However, given the inherent uncertainty of reservoir operation brought by climate change, the compromised strategies selected by conflict-resolution methods can vary. Therefore, quantifying the impacts of climate change on the decision characteristics of conflict-resolution methods can help to address questions about whether conflict-resolution decisions are sustainable given unforeseen changes. In this study, the Yangtze River is regarded as study area. As a world-class hydropower project located on the midstream of Yangtze River, Three Gorges Hydroelectric Power Station can transfer plenty of water energy into electricity. To alleviate the ecological water shortage caused by hydropower operation, sustainable and balanced operation strategies considering the water demands of two departments needs to be studied. In the context of hydropower-environmental conflict-resolution management, the decision behaviors of two fuzzy social choice methods and four game-theoretical bargaining methods under 25 kinds of future climate scenarios are analyzed. Comparing the strategy selection results of different methods for a future period (2021–2082) shows that in all proposed climate scenarios, the decisions of the Nash bargaining method, alternating offer method, and unanimity fallback bargaining method in game-theoretical bargaining methods are more stable than other studied methods, which means that climate change affects the decision behaviors of these three methods slightly. In addition, balanced strategies selected by these three methods could formulate adaptable reservoir operation policies that would satisfy the interests of hydropower and environmental stakeholders equally, and avoid a very low satisfaction level of individual stakeholder and whole stakeholders in the water-conflict year. Therefore, against the background of an increasing demand for environmental protection, these three methods can provide socio-optimal strategies considering social and economic benefits for water resource management.

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Section: Discussionmentioning

confidence: 99%

Assessing the Uncertainty of Hydropower-Environmental Conflict-Resolution Management under Climate Change

Hui

2021

Water

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“…2 b; Supplementary Table S2 ). The selection of ten GCMs can ensure that the median of different combinations generates similar uncertainty components as the whole ensemble 43 . The models were selected according to the skill in reproducing past climate in the region.…”

Section: Methodsmentioning

confidence: 99%

Hydrological droughts in the southern Andes (40–45°S) from an ensemble experiment using CMIP5 and CMIP6 models

Aguayo

León‐Muñoz

Garreaud

et al. 2021

Sci Rep

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The decrease in freshwater input to the coastal system of the Southern Andes (40–45°S) during the last decades has altered the physicochemical characteristics of the coastal water column, causing significant environmental, social and economic consequences. Considering these impacts, the objectives were to analyze historical severe droughts and their climate drivers, and to evaluate the hydrological impacts of climate change in the intermediate future (2040–2070). Hydrological modelling was performed in the Puelo River basin (41°S) using the Water Evaluation and Planning (WEAP) model. The hydrological response and its uncertainty were compared using different combinations of CMIP projects (n = 2), climate models (n = 5), scenarios (n = 3) and univariate statistical downscaling methods (n = 3). The 90 scenarios projected increases in the duration, hydrological deficit and frequency of severe droughts of varying duration (1 to 6 months). The three downscaling methodologies converged to similar results, with no significant differences between them. In contrast, the hydroclimatic projections obtained with the CMIP6 and CMIP5 models found significant climatic (greater trends in summer and autumn) and hydrological (longer droughts) differences. It is recommended that future climate impact assessments adapt the new simulations as more CMIP6 models become available.

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“…The GR4J (Génie Rural à 4 paramètres Journalier) model is a four-parameter lumped and conceptual rainfall-runoff model (Perrin et al, 2003). This model has shown overall good performance in several studies across the globe (Aubert et al, 2003;Raimonet et al, 2018;Riboust et al, 2019;Westra et al, 2014;Youssef et al, 2018). The model requires daily precipitation, temperature and potential evapotranspiration (PET) as inputs to simulate the streamflow.…”

Section: The Gr4j Hydrological Modelmentioning

confidence: 99%

Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies

Mostafa

Brissette²,

Arsenault³

2021

Hydrol. Earth Syst. Sci.

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Abstract. Climate change impact studies require a reference climatological dataset providing a baseline period to assess future changes and post-process climate model biases. High-resolution gridded precipitation and temperature datasets interpolated from weather stations are available in regions of high-density networks of weather stations, as is the case in most parts of Europe and the United States. In many of the world's regions, however, the low density of observational networks renders gauge-based datasets highly uncertain. Satellite, reanalysis and merged product datasets have been used to overcome this deficiency. However, it is not known how much uncertainty the choice of a reference dataset may bring to impact studies. To tackle this issue, this study compares nine precipitation and two temperature datasets over 1145 African catchments to evaluate the dataset uncertainty contribution to the results of climate change studies. These deterministic datasets all cover a common 30-year period needed to define the reference period climate. The precipitation datasets include two gauge-only products (GPCC and CPC Unified), two satellite products (CHIRPS and PERSIANN-CDR) corrected using ground-based observations, four reanalysis products (JRA55, NCEP-CFSR, ERA-I and ERA5) and one merged gauged, satellite and reanalysis product (MSWEP). The temperature datasets include one gauged-only (CPC Unified) product and one reanalysis (ERA5) product. All combinations of these precipitation and temperature datasets were used to assess changes in future streamflows. To assess dataset uncertainty against that of other sources of uncertainty, the climate change impact study used a top-down hydroclimatic modeling chain using 10 CMIP5 (fifth Coupled Model Intercomparison Project) general circulation models (GCMs) under RCP8.5 and two lumped hydrological models (HMETS and GR4J) to generate future streamflows over the 2071–2100 period. Variance decomposition was performed to compare how much the different uncertainty sources contribute to actual uncertainty. Results show that all precipitation and temperature datasets provide good streamflow simulations over the reference period, but four precipitation datasets outperformed the others for most catchments. They are, in order, MSWEP, CHIRPS, PERSIANN and ERA5. For the present study, the two-member ensemble of temperature datasets provided negligible levels of uncertainty. However, the ensemble of nine precipitation datasets provided uncertainty that was equal to or larger than that related to GCMs for most of the streamflow metrics and over most of the catchments. A selection of the four best-performing reference datasets (credibility ensemble) significantly reduced the uncertainty attributed to precipitation for most metrics but still remained the main source of uncertainty for some streamflow metrics. The choice of a reference dataset can therefore be critical to climate change impact studies as apparently small differences between datasets over a common reference period can propagate to generate large amounts of uncertainty in future climate streamflows.

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A Framework to Quantify the Uncertainty Contribution of GCMs Over Multiple Sources in Hydrological Impacts of Climate Change

Cited by 90 publications

References 58 publications

Assessing the Uncertainty of Hydropower-Environmental Conflict-Resolution Management under Climate Change

Assessing the Uncertainty of Hydropower-Environmental Conflict-Resolution Management under Climate Change

Hydrological droughts in the southern Andes (40–45°S) from an ensemble experiment using CMIP5 and CMIP6 models

Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies

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